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About

MiniMax M3.1 Flash is a hosted large language model for developers building coding assistants, AI agents, and software applications. Available through MiniMax’s API and MiniMax Code, it accepts text, image, and video input and generates text responses. Documented uses include code generation and debugging, multi-step reasoning, tool use, codebase and document analysis, and computer-use workflows. The API offers a context window of up to 1 million tokens, adjustable reasoning effort, and OpenAI-compatible and Anthropic-compatible request formats. Usage is billed by input, output, and cached-input tokens. MiniMax provides documentation for API integration and model use. M3.1 Flash is available through the hosted API, M Plan, and MiniMax Code; model weights are planned for a later release.

About

oMLX is a macOS-native MLX server designed to make local AI faster and more practical on Apple Silicon. Built for the way coding agents actually work, it uses paged SSD KV caching to persist cache blocks to disk, allowing previously seen prefixes to be restored across requests and server restarts instead of being recomputed from scratch. This can reduce time to first token on long contexts from 30–90 seconds to under five seconds after the first turn. Continuous batching handles concurrent requests through mlx-lm’s BatchGenerator, improving generation throughput without forcing requests to wait behind a single job. oMLX can serve LLMs, vision-language models, embedding models, and rerankers simultaneously, using LRU eviction when memory runs low. It supports any MLX-format model from Hugging Face, including Qwen, LLaMA, Mistral, Gemma, DeepSeek, MiniMax, and GLM, and can reuse models already stored in the standard Hugging Face cache, LM Studio folders, or custom directories.

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Supported
Linux Not Supported
Cloud Not Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

Software developers and organizations building coding assistants, AI agents, and applications that use a hosted language model.

Audience

Developers and AI power users needing to run fast local LLM inference and agentic coding workflows on Apple Silicon

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Not Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

$0.15/1M input tokens
Input: $0.15 per 1 million tokens; output: $0.60 per 1 million tokens; cached input: $0.015 per 1 million tokens. Standard pay-as-you-go billing in USD, based on token usage.
Free Version Not Supported
Free Trial Not Supported

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Pros & Cons from Real Users

Pros

  • It feels noticeably faster than M3 while still being strong enough for coding, research, computer-use tasks, and longer agent workflows. The 1M-token context window is a big advantage too. I can keep large repos, long documents, screenshots, video context, and a lot of prior agent history in the same session without constantly trimming things down. The pricing is probably the best part. At $0.15 per million input tokens and $0.60 per million output tokens, I can run it heavily without worrying that every agent loop is getting expensive. I also like how much MiniMax improved the agent side. M3.1 Flash is aimed at real multi-step work across coding, enterprise automation, computer use, and even cybersecurity, rather than just fast chat responses.

Cons

  • The main downside is that reasoning is always enabled, so it is not quite as lightweight as a pure instant-response model for trivial tasks.

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

MiniMax
Founded: 2022
China
www.minimax.io/blog/minimax-m31f

Company Information

oMLX
United States
omlx.ai/

Alternatives

Alternatives

Photon

Photon

Moondream
Run BiOS

Run BiOS

UltraSafe AI Inc.
Macyou

Macyou

Macyou LLC
MiniMax M3

MiniMax M3

MiniMax
BaseRT

BaseRT

Base Compute
MiniMax M1

MiniMax M1

MiniMax

Categories

AI Coding Models Supported
AI Models Supported
Foundation Models Supported
Multimodal Models Supported

Categories

AI Inference Supported

Integrations

Claude Code Supported
Model Context Protocol (MCP) Supported
OpenClaw Supported
Alibaba AI Coding Plan Supported
Anthropic Not Supported
BLACKBOX AI Supported
Cline Supported
Cursor Not Supported
GitHub Not Supported
Hermes Agent Supported
Hugging Face Not Supported
MiniMax Not Supported
MiniMax Code Supported
MiniMax Mavis Supported
Mistral AI Not Supported
Ollama Supported
OpenAI Not Supported
OpenCode Zen Supported
OpenTag Supported
Together AI Supported

Integrations

Claude Code Supported
Model Context Protocol (MCP) Supported
OpenClaw Supported
Alibaba AI Coding Plan Not Supported
Anthropic Supported
BLACKBOX AI Not Supported
Cline Not Supported
Cursor Supported
GitHub Supported
Hermes Agent Not Supported
Hugging Face Supported
MiniMax Supported
MiniMax Code Not Supported
MiniMax Mavis Not Supported
Mistral AI Supported
Ollama Not Supported
OpenAI Supported
OpenCode Zen Not Supported
OpenTag Not Supported
Together AI Not Supported
Claim MiniMax M3.1 Flash and update features and information
Claim MiniMax M3.1 Flash and update features and information
Claim oMLX and update features and information
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